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Bayesian survival analysis with INLA.
Alvares, Danilo; van Niekerk, Janet; Krainski, Elias Teixeira; Rue, Håvard; Rustand, Denis.
Afiliação
  • Alvares D; MRC Biostatistics Unit, University of Cambridge, Cambridge, UK.
  • van Niekerk J; Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, Kingdom of Saudi Arabia.
  • Krainski ET; Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, Kingdom of Saudi Arabia.
  • Rue H; Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, Kingdom of Saudi Arabia.
  • Rustand D; Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, Kingdom of Saudi Arabia.
Stat Med ; 43(20): 3975-4010, 2024 Sep 10.
Article em En | MEDLINE | ID: mdl-38922936
ABSTRACT
This tutorial shows how various Bayesian survival models can be fitted using the integrated nested Laplace approximation in a clear, legible, and comprehensible manner using the INLA and INLAjoint R-packages. Such models include accelerated failure time, proportional hazards, mixture cure, competing risks, multi-state, frailty, and joint models of longitudinal and survival data, originally presented in the article "Bayesian survival analysis with BUGS." In addition, we illustrate the implementation of a new joint model for a longitudinal semicontinuous marker, recurrent events, and a terminal event. Our proposal aims to provide the reader with syntax examples for implementing survival models using a fast and accurate approximate Bayesian inferential approach.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Modelos Estatísticos / Teorema de Bayes Limite: Humans Idioma: En Revista: Stat Med Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Modelos Estatísticos / Teorema de Bayes Limite: Humans Idioma: En Revista: Stat Med Ano de publicação: 2024 Tipo de documento: Article
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